Recognition of Articulated and Occluded Objects

A model-based automatic target recognition system is developed to recognize articulated and occluded objects in synthetic aperture radar (SAR) images, based on invariant features of the objects. Characteristics of SAR target image scattering centers, azimuth variation, and articulation invariants are presented. The basic elements of the new recognition system are described and performance results are given for articulated, occluded and occluded articulated objects, and they are related to the target articulation invariance and percent unoccluded.

[1]  Taku Yamazaki,et al.  Invariant histograms and deformable template matching for SAR target recognition , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  M. Werman,et al.  Recognition and localization of articulated objects , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[3]  David Casasent,et al.  SAR detection and recognition filters , 1997, Defense, Security, and Sensing.

[4]  Ming Li,et al.  Target indexing in SAR images using scattering centers and the Hausdorff distance , 1996, Pattern Recognit. Lett..

[5]  Haim J. Wolfson,et al.  Articulated object recognition, or: how to generalize the generalized Hough transform , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Hao Ling,et al.  XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays , 1995, Defense, Security, and Sensing.

[7]  Jacques Verly,et al.  Use of persistent scatterers for model-based recognition , 1994, Defense, Security, and Sensing.

[8]  Azriel Rosenfeld,et al.  Guest Editorial Introduction To The Special Issue On Automatic Target Detection And Recognition , 1997, IEEE Trans. Image Process..

[9]  Christine M. Netishen,et al.  Performance of a High-Resolution Polarimetric SAR Automatic Target Recognition System , 1993 .

[10]  William Grimson,et al.  Object recognition by computer - the role of geometric constraints , 1991 .

[11]  D. Wehner High Resolution Radar , 1987 .

[12]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[13]  Jacques Verly,et al.  Principles and evaluation of an automatic target recognition system for synthetic aperture radar imagery based on the use of functional templates , 1993, Defense, Security, and Sensing.